SR: A Cross-Layer Routing in Wireless Ad Hoc Sensor Networks

SR: A Cross-Layer Routing in SR: A Cross-Layer Routing in Wireless Ad Hoc Sensor Wireless Ad Hoc Sensor NetworksNetworks

Zhen JiangDepartment of Computer Science

West Chester UniversityWest Chester, PA 19335, USA

04/19/23 Hong Kong PolyU

OutlineOutlineIntroduction ProblemOur ApproachConclusion


IntroductionIntroductionRouting problems in WASN applicationsImprovement on the entire routing

path◦Length, delay, and performance◦Security, etc

Topology information model ◦ Where link connections change dynamically◦ For each relay at intermediate nodes

Main factors◦Reliability, scalability, and cost

effectiveness


Existing routing schemesExisting routing schemes

Centralized connection (1) Singe point of failure(2) Hot spots (energy depletion, interference, performance bottle neck, etc)(3) Low reliability (impossible for multi-hop relay in real applications)(4) Low scalability

Not suitable in a highly dense and dynamic

environment


ProblemsProblems


Idea SolutionIdea Solution


ChallengesChallengesUnpredictable configuration ahead

due to◦ Interferences◦ Node failure◦ Node mobility◦ Privacy and selfishness◦ Signal strength and energy consumption ◦ Traffic jamming

Huge cost in probing to catch the configuration change◦ Delay ◦ Information storage◦ Computational cost


ObservationsObservationsReactive information model

◦Not suitable for routing in dynamicsPassive information model

◦Hard to find an effective description for various pair of the source and destination

Information Scale◦The farther the relay node to the

destination, the less accurate information is needed.

◦1-hop direct connection + k-hop reachability information


ProblemProblemA new information model

◦ Indicate the neighbor preference for a 1-hop decision with the global path optimization Existence of such a preference?

◦ Constructed in a passive information model, How to keep relatively stable after dynamic changes

(reliability when link changes and positions of source and destination change)?

◦ Minimize the construction process within a limited area to reduce the cost and to achieve scalability How to ensure a quick converging construction of

such a preference information? How to achieve the global optimization with the

information in those limited areas


Our approachOur approachDescriptor S[0,1]

◦Representative of preference, not ETX metric The higher its value, a better routing path there

likely will be to reach the boundary of the network Used for routing decision to select the successor

with a relatively high index value among all available neighbors Use a single reference (path to network boundary) to reach

the destination Interchangeable use multiple references to approach to the

destination

A tradeoff between cost and accuracy of information!!!

◦S(u) = max { S(n(u)) } Relatively stable and quickly converging


Detailed ProcessDetailed ProcessNetwork ModelInformation Construction

◦Collection and distributionInformation Utilization


Network ModelNetwork Model


Asynchronous MAC Layer Asynchronous MAC Layer SupportSupport

FasterLess synchronization overheadMore accurate to describe the link

status


Neighbor Node Neighbor Node AppearanceAppearance

The appearance of neighbor node v is determined by the Berkeley Mica mote platform as follows, with respect to the distance of link (i.e., D(u, v) = | L(u) − L(v) |).

∈ (0.9, 1], D(u, v) ≤ 10 feet≃ 0, D(u, v) > 40 feet∈ (0, 1), otherwise (1

u→v =


Reachability Reachability Description of 1-hop link qualityDetermined by the Monte Carlo

method◦Ratio of the time that a node v appears

to the total elapsed time ◦Estimated by success REQ/ACK

processes, supported by our asynchronous MAC scheme

Calculated as: {v,u} ≈ u→v × v→u,


Forwarding Zone and Forwarding Zone and Request ZoneRequest Zone


Information ConstructionInformation ConstructionInitialization Phase

◦Each node u outside the interest area sets S(u) to a fixed (1, 1, · · · , 1); otherwise, sets S(u) to a changeable (0, 0, · · · , 0).

◦Then, each node will have stable status by applying

Si(u) = max{{u,v} × Si(v)}, 1 ≤ i ≤ 4 (2

and

Si(u) = max{S’i(u) , {u,v} × Si(v)}, 1 ≤ i ≤ 4 (3

◦Such a link {u, v} is called a key link for Si(u).04/19/23 Hong Kong PolyU

Identification Phase◦Any node u is called a type-i stuck node if it

does not have any neighbor appearing inside forwarding zone Qi. Set Si(u) = 0.

◦Uppon detecting a change of the other end of the key link, a node u with Si(u) > 0 Calculate its type-i status by using Eq. (2) Inform all neighbors its new Si(u) in the next

round If Si(u) = 0, u is called a type-i unsafe node and

no longer change its status; otherwise, u is still type-i safe and Si(u) will eventually stabilize by using Eq. (3).


Self-healing phase◦Any node u (stuck, unsafe, or safe)

will recalculate its Si(u) by using Eq. (3), until the value becomes stable.


Information UtilizationInformation UtilizationIf d n(u), v = d.Determine the request zone Zk(u,

d) (1k 4), according to L(u) and L(d).

Select v n(u)Zk(u, d), where the forwarding from v to d is safe with respect to request zone Zk(v, d).


Routing PropertiesRouting PropertiesA straightforward path can be derived

when the destination d is in one type of safe area. Such a forwarding, say type-i, can be initiated at a source that has a safe successor, i.e., a type-j safe neighbor.

The initiated routing may interrupt when the destination is in an unsafe area and disconnected with the source. Before the retransmission starts, the length of the path approximates to D(s, d) + , where is the maximum length of the boundary circling an unsafe area.


When s is inside an unsafe area, a successful routing will achieve a path shorter than D(s, d) + /2.

If our forwarding advances can reach the destination d with updated safety information, a path can also be constructed with outdated (or lagged) information.

The self-healing phase converges in a limited number of rounds and will not affect any existing safety-information-based routing.


ConclusionsConclusionsTraditional source routing is not applicable

in highly dense and dynamic WASNs.A preference information is more suitable

for forwarding routing, compared with a costly ETX like metric.

Localized method to achieve global optimization in WASN is possible, but is very difficult by the consideration of overhead.

With the support of MAC, a routing without synchronizing neighbors is faster and can allow more concurrent communications, enhancing the network performance.


Thank you!Thank you!Questions and Commons


SR: A Cross-Layer Routing in Wireless Ad Hoc Sensor Networks

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